The phase of plasticity-induced neurochemical changes of high-frequency repetitive transcranial magnetic stimulation are different from visual perceptual learning.

Numerous studies have found that repetitive transcranial magnetic stimulation (rTMS) modulates plasticity. rTMS has often been used to change neural networks underlying learning, often under the assumption that the mechanism of rTMS-induced plasticity should be highly similar to that associated with learning. The presence of visual perceptual learning (VPL) reveals the plasticity of early visual systems, which is formed through multiple phases. Hence, we tested how high-frequency (HF) rTMS and VPL modulate the effect of visual plasticity by investigating neurometabolic changes in early visual areas. We employed an excitatory-to-inhibitory (E/I) ratio, which refers to glutamate concentration divided by GABA+ concentration, as an index of the degree of plasticity. We compared neurotransmitter concentration changes after applying HF rTMS to the visual cortex with those after training in a visual task, in otherwise identical procedures. Both the time courses of the E/I ratios and neurotransmitter contributions to the E/I ratio significantly differed between HF rTMS and training conditions. The peak E/I ratio occurred 3.5 h after HF rTMS with decreased GABA+, whereas the peak E/I ratio occurred 0.5 h after visual training with increased glutamate. Furthermore, HF rTMS temporally decreased the thresholds for detecting phosphene and perceiving low-contrast stimuli, indicating increased visual plasticity. These results suggest that plasticity in early visual areas induced by HF rTMS is not as involved in the early phase of development of VPL that occurs during and immediately after training.

Baseline Cerebro-Cerebellar Functional Connectivity in Afferent and Efferent Pathways Reveal Dissociable Improvements in Visuomotor Learning.

Visuomotor coordination is a complex process involving several brain regions, primarily the cerebellum and motor cortex. Studies have shown inconsistent resting-state functional magnetic resonance imaging (rsfMRI) results in the cerebellar cortex and dentate nucleus of the cerebro-cerebellar connections. Echoing anatomical pathways, these two different cerebellar regions are differentially responsible for afferent and efferent cerebro-cerebellar functional connections. The aim of this study was to measure the baseline resting-state functional connectivity of different cerebellar afferent and efferent pathways and to investigate their relationship to visuomotor learning abilities. We used different cerebellar repetitive transcranial magnetic stimulation (rTMS) frequencies before a pursuit rotor task to influence visuomotor performance. Thirty-eight right-handed participants were included and randomly assigned to three different rTMS frequency groups (1 Hz, 10 Hz and sham) and underwent baseline rsfMRI and pursuit rotor task assessments. We report that greater baseline functional connectivity in the afferent cerebro-cerebellar pathways was associated with greater accuracy improvements. Interestingly, lower baseline functional connectivity in the efferent dentato-thalamo-cortical pathways was associated with greater stability in visuomotor performance, possibly associated with the inhibitory role of the dentate nucleus and caused a reduction in the efferent functional connectivity. The functional dissociation of the cerebellar cortex and dentate nucleus and their connections, suggests that distinct mechanisms in the cerebellum regarding visuomotor learning, which should be investigated in future research.

Frequency-Dependent Effects of Cerebellar Repetitive Transcranial Magnetic Stimulation on Visuomotor Accuracy.

The cerebellum plays a critical role in acquiring visuomotor skills. Visuomotor task mastery requires improving both visuomotor accuracy and stability; however, the cerebellum's contribution to these processes remains unclear. We hypothesized that repetitive transcranial magnetic stimulation (rTMS) of the cerebellum exerts frequency-dependent modulatory effects on both accuracy and stability in subjects performing a visuomotor coordination task (i.e., pursuit rotor task). We recruited 43 healthy volunteers and randomly assigned them to the high-frequency (HF), low-frequency (LF), and sham rTMS groups. We calculated changes in performance of the pursuit rotor task at the highest rotation speed and the minimum distance from target as indices of accuracy. We also calculated the intertrial variability (standard deviations) of time on target and distance from target as indices of stability. Visuomotor accuracy was significantly enhanced in the HF group and disrupted in the LF group compared to the sham group, indicating frequency-dependent effects of rTMS. In contrast, both HF and LF rTMS demonstrated no significant change in visuomotor stability. Surprisingly, our findings demonstrated that the accuracy and stability of visuomotor performance may be differentially influenced by cerebellar rTMS. This suggests that visuomotor accuracy and stability have different underlying neural mechanisms and revealed the possibility of training strategies based on cerebellar neuromodulation.

Synchrony Between Default-Mode and Sensorimotor Networks Facilitates Motor Function in Stroke Rehabilitation: A Pilot fMRI Study.

Stroke is the most common cause of complex disability in Taiwan. After stroke onset, persistent physical practice or exercise in the rehabilitation procedure reorganizes neural assembly for reducing motor deficits, known as neuroplasticity. Neuroimaging literature showed rehabilitative effects specific to the brain networks of the sensorimotor network (SMN) and default-mode network (DMN). However, whether between-network interactions facilitate the neuroplasticity after stroke rehabilitation remains a mystery. Therefore, we conducted the longitudinal assessment protocol of stroke rehabilitation, including three types of clinical evaluations and two types of functional magnetic resonance imaging (fMRI) techniques (resting state and grasp task). Twelve chronic stroke patients completed the rehabilitation protocol for at least 24 h and finished the three-time assessments: before, after rehabilitation, and 1 month after the cessation of rehabilitation. For comparison, age-matched normal controls (NC) underwent the same fMRI evaluation once without repeated measure. Increasing scores of the Fugl-Meyer assessment (FMA) and upper extremity performance test reflected the enhanced motor performances after the stroke rehabilitation process. Analysis of covariance (ANCOVA) results showed that the connections between posterior cingulate cortex (PCC) and iM1 were persistently enhanced in contrast to the pre-rehabilitation condition. The interactions between PCC and SMN were positively associated with motor performances. The enhanced cross-network connectivity facilitates the motor recovery after stroke rehabilitation, but the cross-network interaction was low before the rehabilitation process, similar to the level of NCs. Our findings suggested that cross-network connectivity plays a facilitatory role following the stroke rehabilitation, which can serve as a neurorehabilitative biomarker for future intervention evaluations.

Sensitivity enhancement of task-evoked fMRI using ensemble empirical mode decomposition.

BACKGROUND: Functional magnetic resonance imaging (fMRI) is widely used to investigate dynamic brain functions in neurological and psychological issues; however, high noise level limits its applicability for intensive and sophisticated investigations in the field of neuroscience. NEW METHOD: To deal with both issue (low sensitivity and dynamic signal), we used ensemble empirical mode decomposition (EEMD), an adaptive data-driven analysis method for nonstationary and nonlinear features, to filter task-irrelevant noise from raw fMRI signals. Using both simulations and representative fMRI data, we optimized the analytic parameters and identified non-meaningful intrinsic mode functions (IMFs) to remove noise. RESULTS: We revealed the following advantages of EEMD in fMRI analysis: (1) EEMD achieved high detectability for task engagement; (2) the functional sensitivity was markedly enhanced by removing task-irrelevant artifacts based on EEMD. COMPARISON WITH EXISTING METHOD(S): Compared with other noise-removal methods (e.g., band-pass filtering and independent component analysis), the EEMD-based artifact-removal method exhibited better spatial specificity and superior Gaussianity of the resulting t-score distribution. CONCLUSIONS: We found that EEMD method was efficient to enhance the functional sensitivity of evoked fMRI. The same strategy would be applicable to resting-state fMRI signal in the general purpose.